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A semi-supervised variational Gaussian mixture model

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e188ba1 · Oct 13, 2021

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Application of SsVGMM to medical data-classification with novelty detection (A semi-supervised variational Gaussian mixture model)

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@inproceedings{yang2017application, title={Application of SsVGMM to medical data-classification with novelty detection}, author={Yang, Fan and Soriano, Jaymar and Kubo, Takatomi and Ikeda, Kazushi}, booktitle={Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE}, pages={3098--3101}, year={2017}, organization={IEEE} }

This program can be easily understood from the demo.m file. A dynamic constraint is used in the variational inference, so that a semi-supervised learning can be performed.